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Neuroscience and biobehavioral reviews2020; 113; 1-11; doi: 10.1016/j.neubiorev.2020.02.031

Measuring the evolution of facial ‘expression’ using multi-species FACS.

Abstract: Darwin observed that form, and in his view, meaning, of facial behaviour (observable changes in the appearance of the face, often termed facial 'expression') is similar between a wide range of species and concluded that this must be due to a shared ancestral origin. Yet, as with all social behaviours, exactly how to define similarity and determine homology is debated. Facial behaviour is linked to specific facial muscle movements, so one important factor in determining homology is the anatomical basis of facial behaviours that appear similar in both appearance and social function. The Facial Action Coding System (FACS) was developed for the scientific measurement of human facial behaviour and is based on individual facial muscle movements (Ekman and Friesen, 1978). FACS has since been modified for use with various non-human primate species (chimpanzees, macaques, hylobatids, orangutans) and domestic species (dogs, cats, horses). These FACS can be used to trace continuity of form in facial behaviour across species and build a better understanding of the evolution of facial communication in mammals.
Publication Date: 2020-02-24 PubMed ID: 32105704DOI: 10.1016/j.neubiorev.2020.02.031Google Scholar: Lookup
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  • Journal Article
  • Research Support
  • N.I.H.
  • Extramural
  • Research Support
  • Non-U.S. Gov't
  • Review

Summary

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The research article explores the use of the Facial Action Coding System (FACS) for tracing the evolution and form of facial behaviours across various species, including humans, primates and domestic animals. Essentially, the article dives into the concept put forth by Darwin that facial expressions link back to a shared ancestral origin.

Objective of the Study

  • The core objective of this study was to identify and examine the anatomical basis of similar facial behaviours across different species. Every facial behaviour is associated with specific facial muscle movements. Thus, one crucial factor in identifying commonality or homology is the anatomical foundation of facial behaviours that appear similar in appearance and social function.

Facial Action Coding System (FACS)

  • The researchers employed the Facial Action Coding System (FACS) – a scientific method developed for measuring human facial behaviour based on individual facial muscle movements.
  • Over time, FACS has been adapted for use with various non-human primate species (such as chimpanzees, macaques, hylobatids, orangutans) and domestic animals (like dogs, cats, horses).
  • This system was used to investigate continuity of form in facial behaviour across these species.

Findings and Conclusion

  • Through the use of FACS, the researchers hoped to build a better understanding of the evolution of facial communication in mammals.
  • Tracing the changes and similarities in facial ‘expressions’ across multiple species potentially validates Charles Darwin’s observation of a shared ancestry suggested by common facial behaviour forms.

Cite This Article

APA
Waller BM, Julle-Daniere E, Micheletta J. (2020). Measuring the evolution of facial ‘expression’ using multi-species FACS. Neurosci Biobehav Rev, 113, 1-11. https://doi.org/10.1016/j.neubiorev.2020.02.031

Publication

ISSN: 1873-7528
NlmUniqueID: 7806090
Country: United States
Language: English
Volume: 113
Pages: 1-11
PII: S0149-7634(19)30240-4

Researcher Affiliations

Waller, B M
  • Centre for Comparative and Evolutionary Psychology, Department of Psychology, University of Portsmouth, United Kingdom. Electronic address: bridget.waller@port.ac.uk.
Julle-Daniere, E
  • Centre for Comparative and Evolutionary Psychology, Department of Psychology, University of Portsmouth, United Kingdom.
Micheletta, J
  • Centre for Comparative and Evolutionary Psychology, Department of Psychology, University of Portsmouth, United Kingdom.

MeSH Terms

  • Animals
  • Cats
  • Dogs
  • Face
  • Facial Expression
  • Facial Muscles
  • Horses
  • Primates
  • Social Behavior

Citations

This article has been cited 26 times.
  1. Talwar S, Barbero FM, Calce RP, Collignon O. Automatic Brain Categorization of Discrete Auditory Emotion Expressions.. Brain Topogr 2023 Aug 28;.
    doi: 10.1007/s10548-023-00983-8pubmed: 37639111google scholar: lookup
  2. Cascella M, Schiavo D, Cuomo A, Ottaiano A, Perri F, Patrone R, Migliarelli S, Bignami EG, Vittori A, Cutugno F. Artificial Intelligence for Automatic Pain Assessment: Research Methods and Perspectives.. Pain Res Manag 2023;2023:6018736.
    doi: 10.1155/2023/6018736pubmed: 37416623google scholar: lookup
  3. Lim C, Inagaki M, Shinozaki T, Fujita I. Analysis of convolutional neural networks reveals the computational properties essential for subcortical processing of facial expression.. Sci Rep 2023 Jul 5;13(1):10908.
    doi: 10.1038/s41598-023-37995-0pubmed: 37407668google scholar: lookup
  4. Long H, Peluso N, Baker CI, Japee S, Taubert J. A database of heterogeneous faces for studying naturalistic expressions.. Sci Rep 2023 Apr 3;13(1):5383.
    doi: 10.1038/s41598-023-32659-5pubmed: 37012369google scholar: lookup
  5. Boneh-Shitrit T, Feighelstein M, Bremhorst A, Amir S, Distelfeld T, Dassa Y, Yaroshetsky S, Riemer S, Shimshoni I, Mills DS, Zamansky A. Explainable automated recognition of emotional states from canine facial expressions: the case of positive anticipation and frustration.. Sci Rep 2022 Dec 30;12(1):22611.
    doi: 10.1038/s41598-022-27079-wpubmed: 36585439google scholar: lookup
  6. Terhürne P, Schwartz B, Baur T, Schiller D, Eberhardt ST, André E, Lutz W. Validation and application of the Non-Verbal Behavior Analyzer: An automated tool to assess non-verbal emotional expressions in psychotherapy.. Front Psychiatry 2022;13:1026015.
    doi: 10.3389/fpsyt.2022.1026015pubmed: 36386975google scholar: lookup
  7. Escelsior A, Amadeo MB, Esposito D, Rosina A, Trabucco A, Inuggi A, Pereira da Silva B, Serafini G, Gori M, Amore M. COVID-19 and psychiatric disorders: The impact of face masks in emotion recognition face masks and emotion recognition in psychiatry.. Front Psychiatry 2022;13:932791.
    doi: 10.3389/fpsyt.2022.932791pubmed: 36238943google scholar: lookup
  8. Merkies K, Sudarenko Y, Hodder AJ. Can Ponies (Equus Caballus) Distinguish Human Facial Expressions?. Animals (Basel) 2022 Sep 7;12(18).
    doi: 10.3390/ani12182331pubmed: 36139191google scholar: lookup
  9. Davila-Ross M, Palagi E. Laughter, play faces and mimicry in animals: evolution and social functions.. Philos Trans R Soc Lond B Biol Sci 2022 Nov 7;377(1863):20210177.
    doi: 10.1098/rstb.2021.0177pubmed: 36126662google scholar: lookup
  10. Kret ME, Massen JJM, de Waal FBM. My Fear Is Not, and Never Will Be, Your Fear: On Emotions and Feelings in Animals.. Affect Sci 2022 Mar;3(1):182-189.
    doi: 10.1007/s42761-021-00099-xpubmed: 36042781google scholar: lookup
  11. Leconstant C, Spitz E. Integrative Model of Human-Animal Interactions: A One Health-One Welfare Systemic Approach to Studying HAI.. Front Vet Sci 2022;9:656833.
    doi: 10.3389/fvets.2022.656833pubmed: 35968006google scholar: lookup
  12. Clark PR, Waller BM, Agil M, Micheletta J. Crested macaque facial movements are more intense and stereotyped in potentially risky social interactions.. Philos Trans R Soc Lond B Biol Sci 2022 Sep 26;377(1860):20210307.
    doi: 10.1098/rstb.2021.0307pubmed: 35934960google scholar: lookup
  13. Holler J. Visual bodily signals as core devices for coordinating minds in interaction.. Philos Trans R Soc Lond B Biol Sci 2022 Sep 12;377(1859):20210094.
    doi: 10.1098/rstb.2021.0094pubmed: 35876208google scholar: lookup
  14. Kavanagh E, Kimock C, Whitehouse J, Micheletta J, Waller BM. Revisiting Darwin's comparisons between human and non-human primate facial signals.. Evol Hum Sci 2022;4.
    doi: 10.1017/ehs.2022.26pubmed: 35821665google scholar: lookup
  15. Feighelstein M, Shimshoni I, Finka LR, Luna SPL, Mills DS, Zamansky A. Automated recognition of pain in cats.. Sci Rep 2022 Jun 10;12(1):9575.
    doi: 10.1038/s41598-022-13348-1pubmed: 35688852google scholar: lookup
  16. Dollion N, Grandgeorge M, Saint-Amour D, Hosein Poitras Loewen A, François N, Fontaine NMG, Champagne N, Plusquellec P. Emotion Facial Processing in Children With Autism Spectrum Disorder: A Pilot Study of the Impact of Service Dogs.. Front Psychol 2022;13:869452.
    doi: 10.3389/fpsyg.2022.869452pubmed: 35668968google scholar: lookup
  17. Correia-Caeiro C, Burrows A, Wilson DA, Abdelrahman A, Miyabe-Nishiwaki T. CalliFACS: The common marmoset Facial Action Coding System.. PLoS One 2022;17(5):e0266442.
    doi: 10.1371/journal.pone.0266442pubmed: 35580128google scholar: lookup
  18. Inagaki M, Inoue KI, Tanabe S, Kimura K, Takada M, Fujita I. Rapid processing of threatening faces in the amygdala of nonhuman primates: subcortical inputs and dual roles.. Cereb Cortex 2023 Jan 5;33(3):895-915.
    doi: 10.1093/cercor/bhac109pubmed: 35323915google scholar: lookup
  19. Morozov A, Parr LA, Gothard K, Paz R, Pryluk R. Automatic Recognition of Macaque Facial Expressions for Detection of Affective States.. eNeuro 2021 Nov-Dec;8(6).
    doi: 10.1523/ENEURO.0117-21.2021pubmed: 34799408google scholar: lookup
  20. Mielke A, Waller BM, Pérez C, Rincon AV, Duboscq J, Micheletta J. NetFACS: Using network science to understand facial communication systems.. Behav Res Methods 2022 Aug;54(4):1912-1927.
    doi: 10.3758/s13428-021-01692-5pubmed: 34755285google scholar: lookup
  21. Jarvis S, Ellis MA, Turnbull JF, Rey Planellas S, Wemelsfelder F. Qualitative Behavioral Assessment in Juvenile Farmed Atlantic Salmon (Salmo salar): Potential for On-Farm Welfare Assessment.. Front Vet Sci 2021;8:702783.
    doi: 10.3389/fvets.2021.702783pubmed: 34557541google scholar: lookup
  22. Alais D, Xu Y, Wardle SG, Taubert J. A shared mechanism for facial expression in human faces and face pareidolia.. Proc Biol Sci 2021 Jul 14;288(1954):20210966.
    doi: 10.1098/rspb.2021.0966pubmed: 34229489google scholar: lookup
  23. Steinmair D, Löffler-Stastka H. The Emerging Role of Interdisciplinarity in Clinical Psychoanalysis.. Front Psychol 2021;12:659429.
    doi: 10.3389/fpsyg.2021.659429pubmed: 34025523google scholar: lookup
  24. Correia-Caeiro C, Guo K, Mills D. Bodily emotional expressions are a primary source of information for dogs, but not for humans.. Anim Cogn 2021 Mar;24(2):267-279.
    doi: 10.1007/s10071-021-01471-xpubmed: 33507407google scholar: lookup
  25. Neethirajan S, Reimert I, Kemp B. Measuring Farm Animal Emotions-Sensor-Based Approaches.. Sensors (Basel) 2021 Jan 14;21(2).
    doi: 10.3390/s21020553pubmed: 33466737google scholar: lookup
  26. Correia-Caeiro C, Holmes K, Miyabe-Nishiwaki T. Extending the MaqFACS to measure facial movement in Japanese macaques (Macaca fuscata) reveals a wide repertoire potential.. PLoS One 2021;16(1):e0245117.
    doi: 10.1371/journal.pone.0245117pubmed: 33411716google scholar: lookup